Sridhar Ravi’s research while affiliated with University of South Wales and other places

Biological undulatory swimmers display a wide range of gaits and are adept at swimming in different directions. This study explores the impact of passive dynamics as a result of fluid–structure interaction on the gaits of a model swimmer through computational simulations. Inspired by slender-bodied natural aquatic swimmers, the model consists of a flexible body and a rigid head. Systematically varying body stiffness and head pitching, the research replicates various swimming patterns observed in nature (both forward and backward). Optimal forward gaits, akin to anguilliformes and carangiformes, result from low to high bending rigidity and small pitching amplitudes. Conversely, low bending rigidity with high pitching amplitude produces backward swimming (tail-first), similar to mosquito larvae, exhibiting unique flow-field features and generating backward propulsion forces. The study underscores the significant role of passive dynamics in undulatory swimming and the potential for diverse gait generation through tailored structural and kinematic design in bio-inspired devices.

Rejecting perturbations is an essential ability of an aircraft while operating in a gusty environment, especially for urban uncrewed aerial vehicles (UAVs) in complex aerodynamics within a city environment. This paper presents a passively pitching wing tested as a mechanical means of mitigating the adverse effects of gust conditions during UAV flight. A wind tunnel model of a NACA0015 airfoil with a hinged, variable torsional stiffness pitch axis was designed, fabricated, and experimentally investigated. The gust alleviation characteristics were examined under continuous gust flow conditions of varying frequencies at different pitch angles. The gust responses of the pitching wing were compared with a non-pitching baseline wing. The spring-hinged pitching wing has a significant impact on the gust loading and possesses a unique dynamic behaviour with varying gust reduced frequency. The results indicate a correlation between the spring dynamics, gust reduced frequency, and gust load alleviation. This study contributes insights into the literature on developing small fixed-wing UAVs capable of operating in gusty dynamic environments.

The ability to fly through openings in vegetation allows insects like bees to access otherwise unreachable food sources. The specific visual strategies employed by flying insects during aperture negotiation tasks remain unknown. In this study, we investigated the visual and geometric parameters of apertures that influence honeybee flight. We recorded honeybees flying through apertures with varying shapes and sizes using high-speed cameras to examine their spatial distribution patterns and trajectories during passage. Our results reveal that the flight of bees was, on average, along the bilateral center of the edges of the aperture irrespective of the size. When apertures were smaller, bees tended to also fly closer to the vertical center. However, for larger apertures, they traverse at lower vertical positions (closer to the bottom edge). The behaviors suggest that honeybees modulate their flight trajectories in response to spatial constraints, adjusting trajectory relative to aperture dimensions. When entering at off-center horizontal positions, bees tended to access the vertical center of the aperture, indicating altitude selection influenced by the curvature of the edge below. This behavior suggests an acute awareness of the vertical and horizontal spatial constraints and a preference for maintaining a curvature-dependent altitude that optimizes safe passage. Our analysis reveals that honeybees modulate speed and altitude above the ventral edge passing beneath them, maintaining a median ventral optic flow of 778 deg/s. This relationship suggests a control mechanism where bees rely on visual information in a narrow ventrally directed field to navigate safely through confined spaces.

The effects of the twisting-induced variation in the effective angle of attack, α e f f , on the aerodynamics and the leading edge vortex (LEV) of a flapping wing are investigated using the lattice Boltzmann method (LBM) and an immersed boundary method (IBM). If the wing is rigid during the flapping flight, α e f f of the outer portion of the wing would exceed a reasonable range. Wing deformation has been known to be able to improve flight efficiency, which adjusts α e f f along the wing span to maintain it within a reasonable range during flapping flight. In the simulations, the maximum α e f f at the wing tip is set from 9 • to 54 • in steps of 9 • in this work. It is found that the wing achieves the highest propulsive efficiency by reallocating the force production in the streamwise and spanwise directions when the maximum α e f f at the wing tip is 27 • .

Propeller-driven aerial vehicles have recently attracted interest for potential applications in extraterrestrial exploration at significantly lower atmospheric pressures than Earth. This study investigates the effects of Reynolds number and blade angle on the propeller performance at low pressures. Experiments are performed on a two-blade rotor in a vacuum chamber. Based on the measured thrust and torque, the performance is evaluated in terms of the thrust-to-power ratio and figure of merit. The blade angle affects the wing performance at all pressures, as expected. However, the Reynolds number shows a significant influence on the thrust and power coefficients only at very low pressures ∼ 3 kPa. Broadly, the study concludes that both the blade angle and Reynolds number are found to be important for propeller aerodynamics in very low-pressure environments.

This study aims to develop and validate an efficient numerical method to investigate compressible flows in fluid-structure interaction scenarios, such as vortex-induced vibrations in a bluff body or flapping wings. Inspired by the simplicity and robustness of the lattice Boltzmann method (LBM), it has been extended to com-pressible flows involving fluid-structure interactions. Because of the intrinsic parallel nature, it stands at the forefront of solving many industrial problems when coupled with immersed boundary methods (IBM). However , the conventional scheme is still not well suited for high-speed flows. In this study, we developed a hybrid compressible LBM approach, using LBM for the mass and momentum equations and the finite difference method (FDM) for the energy equation, alongside an penalty IBM. The well-known Mach cubic error for high-speed flows is corrected using a forcing term along with penalty IB forces, and a hybrid recursive regularized collision model based on the pressure-based method has been used to maintain accuracy and stability in highly compressible flows. For validation, subsonic, and supersonic flow over a 2D circular cylinder, as well as tran-sonic flow over a NACA airfoil, are presented. The current findings show good agreement with previously published data derived from alternative methodologies, validating the effectiveness of the proposed approach in simulating highly compressible flows.

This work presents a numerical method for modeling fluid–structure–acoustics interaction (FSAI) problems involving large deformation. The method incorporates an immersed boundary method and a regularized lattice Boltzmann method (LBM) where a multi-block technique and a nonreflecting boundary condition are implemented. The von Neumann analysis is conducted to investigate the stability of the regularized LBM. It is found that the accuracy and stability of the regularized LBM can be improved when the collision operator is computed from the Hermite polynomials up to the fourth order instead of the second order. To validate the present method, four benchmark cases are conducted: the propagation of an acoustic monopole point source, the sound generated by a stationary cylinder in a uniform flow, the sound generation of a two-dimensional insect model in hovering flight, and the sound generation of a three-dimensional flapping wing. Predictions given by the current method show a good agreement with numerical simulations and analytical solutions reported in the literature, demonstrating its capability of solving FSAI problems involving complex geometries and large deformation. Finally, the method is applied in modeling sound generation in vortex-induced vibrations of a rigid cylinder and a sphere. It is found that vortex-induced vibration can enhance the acoustic intensity by approximately four times compared to that of the stationary case for a cylinder. In contrast, both vibrating and stationary spheres exhibited relatively less intense noise, primarily within the wake. Notably, the spanwise noise propagation is only observed when the sphere is vibrating.

In prior research, we analyzed the backwards swimming motion of mosquito larvae, parameterized it, and replicated it in a Computational Fluid Dynamics (CFD) model. Since the parameterized swimming motion is copied from observed larvae, it is not necessarily the most efficient locomotion for the model of the swimmer. In this project, we further optimize this copied solution for the swimmer model. We utilize Reinforcement Learning to guide local parameter updates. Since the majority of the computation cost arises from the CFD model, we additionally train a deep learning model to replicate the forces acting on the swimmer model. We find that this method is effective at performing local search to improve the parameterized swimming locomotion.